Counter-Trend Trading

In Research on October 27, 2012 at 12:09 pm

I really enjoyed this research report from 361 Capital called “Counter-Trend Trading”, written by Nick Libertini.  A pdf is attached below (please respect the author’s rights as described therein).

The white paper compares short term momentum strategies and counter-trend strategies.  Specifically it references research from The Conners Group on the S&P500 and other equity indices and compares the returns for some short term trend and counter trend strategies from 1990-2011.  I was fascinated by the Noise Statistic and calculations provided that show how “noise” has increased in the last decades.  The report also discusses investing models generally and showed an excellent table of investing models (figure 5 in the paper).

I had a couple of issues with the research, which, if solved, would have made it even better:

1. [Updated to accurately describe the holding periods which was incorrect in an earlier version] The strategies used were 1, 3, 5, and 10 day new high and new low strategies, with a 1-10 day hold period.  These timeframes are so short, and the hold period is so short, they will intuitively favour counter-trend strategies.  The results, indeed, showed that counter-trend strategies lead to higher returns.  However to capture returns from a trend or real momentum, it must be held for longer.  It would have been fascinating to expand the test to include 20, 50, and 100 day new high/low strategies, and to test hold periods across the spectrum (1, 3, 5, 10, 20, 50, 100 day).  This seems like an oversight, and it would have been easy to do since there was 20 years of data to work with.  Without this info, the “comparison” of momentum to counter-trend falls flat, even though the counter-trend stats by themselves are interesting.

(more below)

2. The markets that were tested were the S&P500, Nasdaq 100, Russell 2000, Nikkei 225, and Euro Stoxx 50, and the author concludes that the counter-trend theory “holds up across several markets”.  However, these markets are so highly correlated (large-cap equities) that such a conclusion cannot be drawn.  The test could have included, say, 2 large cap equity indices, 2 soft commodities, 2 metals, 2 currencies, and 2 credit markets.  That would have really tested if it holds up across “several markets”.  The white paper opens and closes by talking about managed futures strategies that CTAs typically use, which necessarily includes many very diverse markets (sometimes as many as 50-100 uncorrellated markets) – it didn’t make sense to then test only large cap equities.

3. Lastly, there was a good discussion about why markets exhibit irrational pricing and why prices tend to move above and below fundamental value, but it doesn’t say that the primary reason is that fundamental value cannot be defined or agreed on by all or even a majority of participants at the same time.  We can only ever estimate what fundamental value is (or was), therefore prices will necessarily be a little (or a lot) above or below fundamental value at any moment in time.  It is easier to tell what fundamental value was (or should have been) at a point in the past, but it is never possible to do so in real time.

Despite some reservations, I recommend reading the report and I got a lot out of it.

[Addendum- I was going back through some book review notes and remembered that Dr Alexander Elder has his own market noise statistic, which is the average price range below the previous day’s low in an up-trend, or the average price range above the previous day’s high in a down-trend.  However calculated, this is a useful statistic that i will start paying attention to.]


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